Discrepancy between Gradients Derived by Cardiac Catheterization and by Doppler Echocardiography in Aortic Stenosis: How Often Does Pressure Recovery Play a Role?

Patient-specific fluid simulation of transcatheter mitral valve replacement in mitral annulus calcification

Introduction

Transcatheter mitral valve replacement is a promising alternative to open-heart surgery in elderly patients. Patients with severe mitral annulus calcification (MAC) are a particularly high-risk population, where postprocedural complications can have catastrophic effects. Amongst these, obstruction of the left ventricular outflow tract can lead to ventricular hypertrophic remodeling and subsequent heart failure, while subclinical valve thrombosis can result in early bioprosthetic valve failure.

Methods

To elucidate the mechanisms of left ventricular outflow tract obstruction and valve thrombosis following valve-in-MAC procedures, we used image processing and Computational Fluid Dynamics (CFD) software to generate patient- and device-specific models based on preprocedural CT data. Personalized computer simulations were performed to predict the left ventricular haemodynamics after implantation in three patients with severe MAC.

Results

The simulations have successfully captured the increased pressure gradient in the left ventricular outflow tract as a result of the partial obstruction due to the implanted valve. Regions of wall shear stress above the threshold value for platelet activation were also observed on the bioprosthetic frame as a result of the reduced outflow tract area, which led to increases in flow resistance and blood residence time inside the ventricle. Consistent with these findings, areas of slow recirculating flow and blood stasis formed near the valve frame, creating potential pro-thrombotic conditions.

Discussion

This study provides insight into the relationship between size and shape of the outflow tract post-implantation, pressure gradients and pro-thrombotic flow metrics such as wall shear stress and blood residence time. Results show the potential of CFD modeling to bring key functional metrics into preprocedural assessment for a comprehensive evaluation of post-procedural risks beyond anatomical factors. Following further validation and extension to the atrial chamber, this approach can provide an in-depth analysis of the likelihood of valvular thrombosis.

Validation of aortic valve pressure gradient quantification using semi-automated 4D flow CMR pipeline

OBJECTIVE

Doppler echocardiographic aortic valve peak velocity and peak pressure gradient assessment across the aortic valve (AV) is the mainstay for diagnosing aortic stenosis. Four-dimensional flow cardiovascular magnetic resonance (4D flow CMR) is emerging as a valuable diagnostic tool for estimating the peak pressure drop across the aortic valve, but assessment remains cumbersome. We aimed to validate a novel semi-automated pipeline 4D flow CMR method of assessing peak aortic value pressure gradient (AVPG) using the commercially available software solution, CAAS MR Solutions, against invasive angiographic methods.

RESULTS

We enrolled 11 patients with severe AS on echocardiography from the EurValve programme. All patients had pre-intervention doppler echocardiography, invasive cardiac catheterisation with peak pressure drop assessment across the AV and 4D flow CMR. The peak AVPG was 51.9 ± 35.2 mmHg using the invasive pressure drop method and 52.2 ± 29.2 mmHg for the 4D flow CMR method (semi-automated pipeline), with good correlation between the two methods (r = 0.70, p = 0.017). Assessment of AVPG by 4D flow CMR using the novel semi-automated pipeline method shows excellent agreement to invasive assessment when compared to doppler-based methods and advocate for its use as complementary to echocardiography.

Computed Tomography-Based Assessment of Transvalvular Pressure Gradient in Aortic Stenosis

Background: In patients with aortic stenosis, computed tomography (CT) provides important information about cardiovascular anatomy for treatment planning but is limited in determining relevant hemodynamic parameters such as the transvalvular pressure gradient (TPG).

Purpose: In the present study, we aimed to validate a reduced-order model method for assessing TPG in aortic stenosis using CT data.

Methods: TPG_CT was calculated using a reduced-order model requiring the patient-specific peak-systolic aortic flow rate (Q) and the aortic valve area (AVA). AVA was determined by segmentation of the aortic valve leaflets, whereas Q was quantified based on volumetric assessment of the left ventricle. For validation, invasively measured TPG_catheter was calculated from pressure measurements in the left ventricle and the ascending aorta. Altogether, 84 data sets of patients with aortic stenosis were used to compare TPG_CT against TPG_catheter.

Results: TPG_catheter and TPG_CT were 50.6 ± 28.0 and 48.0 ± 26 mmHg, respectively (p = 0.56). A Bland–Altman analysis revealed good agreement between both methods with a mean difference in TPG of 2.6 mmHg and a standard deviation of 19.3 mmHg. Both methods showed good correlation with r = 0.72 (p < 0.001).

Conclusions: The presented CT-based method allows assessment of TPG in patients with aortic stenosis, extending the current capabilities of cardiac CT for diagnosis and treatment planning.

Validation of four-dimensional flow cardiovascular magnetic resonance for aortic stenosis assessment

The management of patients with aortic stenosis (AS) crucially depends on accurate diagnosis. The main aim of this study were to validate the four-dimensional flow (4D flow) cardiovascular magnetic resonance (CMR) methods for AS assessment. Eighteen patients with clinically severe AS were recruited. All patients had pre-valve intervention 6MWT, echocardiography and CMR with 4D flow. Of these, ten patients had a surgical valve replacement, and eight patients had successful transcatheter aortic valve implantation (TAVI). TAVI patients had invasive pressure gradient assessments. A repeat assessment was performed at 3–4 months to assess the remodelling response. The peak pressure gradient by 4D flow was comparable to an invasive pressure gradient (54 ± 26 mmHG vs 50 ± 34 mmHg, P = 0.67). However, Doppler yielded significantly higher pressure gradient compared to invasive assessment (61 ± 32 mmHG vs 50 ± 34 mmHg, P = 0.0002). 6MWT was associated with 4D flow CMR derived pressure gradient (r = −0.45, P = 0.01) and EOA (r = 0.54, P < 0.01) but only with Doppler EOA (r = 0.45, P = 0.01). Left ventricular mass regression was better associated with 4D flow derived pressure gradient change (r = 0.64, P = 0.04). 4D flow CMR offers an alternative method for non-invasive assessment of AS. In addition, 4D flow derived valve metrics have a superior association to prognostically relevant 6MWT and LV mass regression than echocardiography.